Photorealistic full-body Codec Avatars [1]}, [2]} and physics-based cloth simulation [3]} have been extensively explored in existing literature. For these two modules we mostly follow previous work and provide implementation detail in the supplementary documentFor the results in this paper, we use a GPU-based XPBD cloth simulation of spring-mass system for its superior runtime performance, but our method is not restricted to a specific choice of simulators.. We find efficient photorealistic appearance modeling of clothing to be a critical missing component in such a pipeline, and we tackle two major technical challenges in order to build such a system. On the one hand, as explained in Sec. , we develop a deep clothing appearance model that can efficiently generate highly photorealistic clothing texture with dynamic view-dependent and shadowing effects. For the design of the model, we focus on the generalization of the produced appearance, since the input geometry from the cloth simulator can be different from the tracked clothing geometry used to train the appearance model. On the other hand, in order to generate training data for the appearance model, we extend the previous clothing registration algorithm [2]}, [5]} to handle highly dynamic clothing types including a skirt and a dress. In addition, we track photometric correspondences on the garments by matching salient features, which are essential for the modeling of highly textured clothing appearance. The clothing registration step is described in Sec. .
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